Title :
An Overview of Intrusion Detection Based on Data Mining Techniques
Author :
Wankhade, K. ; Patka, S. ; Thool, R.
Author_Institution :
Dept. of Inf. Technol., G.H. Raisoni Coll. of Eng., Nagpur, India
Abstract :
Intrusion Detection System (IDS) is a vital component of any network in today´s world of Internet. IDS are an effective way to detect different kinds of attacks in interconnected network. An effective Intrusion Detection System requires high accuracy and detection rate as well as low false alarm rate. Different Data Mining techniques such as clustering and classification are proving to be useful for analyzing and dealing with large amount of network traffic. This paper presents various data mining techniques applied on intrusion detection systems for the effective identification of both known and unknown patterns of attacks, to develop secure information systems.
Keywords :
data mining; pattern classification; pattern clustering; security of data; IDS; Internet; attack detection; attack pattern identification; classification; clustering; data mining; detection rate; false alarm rate; interconnected network; intrusion detection system; network traffic; secure information system; Classification algorithms; Clustering algorithms; Conferences; Data mining; Heuristic algorithms; Intrusion detection; Labeling; Intrusion detection system; classification; clustering; data mining; detection rate; false alarm rate;
Conference_Titel :
Communication Systems and Network Technologies (CSNT), 2013 International Conference on
Conference_Location :
Gwalior
Print_ISBN :
978-1-4673-5603-9
DOI :
10.1109/CSNT.2013.134
